Forecasting and operational assessment of the quality of repaired units

Abstract

Evaluation alone is not enough to improve product quality. It is necessary to have not only the estimated indicator itself, but also to declare the factors that influence the formation of quality and to investigate this influence. Only then does it become possible to carry out quality management. To study the quality of repaired products, we use the economic and statistical method, which is as follows. Product quality is considered in two aspects: production and consumer. Manufacturing quality is a set of product properties (physical, chemical, physical and mechanical, etc.) obtained by it in the process of manufacturing or repair. The consumer quality of products manifests itself in the process of consumption (operation) and is determined by the cumulative impact of all characteristics of production quality and conditions of consumption. With the help of the correlation level, two main tasks can be solved: operational quality assessment at the stage of production (repair), based on predicting the consumer quality of the projection according to the known values of its production quality indicators; management of the production quality of products in accordance with a given level of its consumer quality. The most characteristic indicators of the production quality of the repaired units are the errors in the dimensions of the shape of parts, the relative position of their surfaces, the size of the washed out links of the dimensional chains of mechanisms, the physical and mechanical properties of materials, etc. At the repair enterprise, by means of appropriate measurements, the values of the indicators of the production quality of batches of products are determined. Then, in operation, these products are monitored in order to determine their consumer quality. The consumer quality of repaired products can be expressed by a number of indicators, but the most expedient is the use of such an indicator as winding to the first failure caused by aging processes (wear, fatigue failure, etc.). Considering the above, research aimed at predicting and quickly assessing the quality of repaired units is an urgent problem.